crdt-merge 0.9.4

Mathematically proven conflict-free merge for AI model weights, datasets, and agent memory. Zero dependencies. Patent pending.

crdt-merge

The first merge library where every operation is mathematically guaranteed to converge.
Tabular data. Neural network weights. Distributed agents. One unified CRDT layer.

pip install crdt-merge

Documentation · Quick Start · API Reference · Architecture · Changelog

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Every merge algorithm you use is broken. This one isn't.

Every standard merge strategy — weight averaging, SLERP, TIES, DARE, Fisher — fails at least one of the three algebraic laws required for distributed convergence. This isn't an implementation bug. It's mathematically provable. crdt-merge is the fix: a patented two-layer architecture that makes any merge strategy — including inherently stochastic and non-commutative ones — fully CRDT-compliant.

The result: 26 strategies, all guaranteed to produce identical output regardless of merge order, grouping, or duplication. No coordination. No locking. No central arbiter.

Patent Pending — UK Application No. 2607132.4

How it works — full architecture, mathematical proofs, and the 7 architectures we evaluated →

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What you can do with it

Federated Model Merging Without a Parameter Server

100 hospitals train locally, merge globally — no coordinator, no single point of failure. Any node can produce the final model. Late arrivals are absorbed automatically. Guide →

Convergent Multi-Agent AI

Agents share and merge beliefs via CRDT state — no orchestrator picks winners. Works offline, across partitions, at any scale. Guide →

Privacy-Preserving Merge

Merge encrypted data without decryption. Four AEAD backends. The merging party never sees plaintext. Guide →

The Right to Forget in Trained Models

GDPR erasure in milliseconds — surgically remove a contributor's influence without retraining. Guide →

MergeQL — Query Language for Distributed Knowledge

SQL-like syntax for CRDT-correct multi-source merges with full provenance. Guide →

Provenance-Complete AI

Per-field, per-decision audit trail — SHA-256 hash-chained, tamper-evident, EU AI Act ready. Guide →

LoRA Adapter Merging

Mixed-rank adapters merged with per-module strategy selection and SVD rank harmonization. Guide →

Continual Learning Without Catastrophic Forgetting

Absorb new tasks as post-training merges — no data replay, no model growth, full knowledge retention. Guide →

Gossip Protocol Sync

Serverless state convergence via digest-based anti-entropy. You provide the transport. Guide →

Probabilistic CRDTs at Planetary Scale

HyperLogLog, Bloom filters, Count-Min Sketch — all natively CRDT-mergeable across 500+ nodes. Guide →

Delta Sync & Merkle Verification

Ship only what changed. Prove convergence in O(log n). Guide →

Runtime CRDT Verification

Property-based proof that any merge function satisfies all three laws. Catches violations at import time. Guide →

Agentic Memory at Scale

O(1) dedup across 1M+ agent memories. Budget-aware context merge. Crash recovery from peers. Guide →

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Quick Start

# Tabular
from crdt_merge import CRDTDataFrame
merged = CRDTDataFrame(df_a, node_id="a").merge(CRDTDataFrame(df_b, node_id="b"))

# Model weights
from crdt_merge.model import CRDTMergeState
state = CRDTMergeState()
state.add("model-a", weights_a)
state.add("model-b", weights_b)
merged = state.merge(strategy="slerp")  # order of add() never matters

# Verify any merge function
from crdt_merge import verified_merge

@verified_merge
def my_merge(a, b):
    return your_logic(a, b)  # raises CRDTViolationError if laws are broken

Full API reference →

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Installation

pip install crdt-merge            # Core — zero dependencies
pip install crdt-merge[fast]      # DuckDB + Polars (38.8× on A100)
pip install crdt-merge[model]     # PyTorch model weights
pip install crdt-merge[crypto]    # AEAD encryption backends
pip install crdt-merge[all]       # Everything

Zero required dependencies. Python 3.9–3.12. Linux, macOS, Windows.

All install options →

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By the Numbers

Test suite	3,041 tests, 0 failures
CRDT compliance tests	1,200 / 1,200
Merge strategies	26
CRDT overhead	< 0.5ms per merge
Model speedup vs. naive	38.8×
Encryption backends	4
Architectures evaluated	7 → 1 winner

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Cross-Language Ports

Language	Package	Status
Python (reference)	crdt-merge v0.9.4	Full feature set
Rust	crdt-merge v0.2.0	Core CRDTs + merge
TypeScript	crdt-merge v0.2.0	Core CRDTs + merge
Java	crdt-merge v0.2.0	Source complete

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License

BSL 1.1 → automatically converts to Apache 2.0 on 29 March 2028.

Free for research, personal use, and most production use. Source-available. Not free for competing commercial merge-as-a-service.

The PATENTS file includes a defensive patent grant (UK Application 2607132.4). See LICENSE, CLA.

Copyright 2026 Ryan Gillespie. Commercial licensing: [e-mail] · [e-mail]

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Documentation · Architecture · API Reference · Guides · Changelog · License

Built by Ryan Gillespie / Optitransfer